analyses:stijnen2010
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analyses:stijnen2010 [2021/10/22 14:45] – Wolfgang Viechtbauer | analyses:stijnen2010 [2022/08/03 11:22] (current) – Wolfgang Viechtbauer | ||
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dat | dat | ||
</ | </ | ||
- | (I copy the dataset into '' | + | (I copy the dataset into '' |
<code output> | <code output> | ||
| | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 17) = 72.166, p-val < .001 | Q(df = 17) = 72.166, p-val < .001 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -3.302 | + | -3.302 |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 17) = 23.671, p-val = 0.129 | Q(df = 17) = 23.671, p-val = 0.129 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -4.260 | + | -4.260 |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 17) = 69.103, p-val < .001 | Wld(df = 17) = 69.103, p-val < .001 | ||
LRT(df = 17) = 85.284, p-val < .001 | LRT(df = 17) = 85.284, p-val < .001 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -3.496 | + | -3.496 |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 17) = 16.145, p-val = 0.514 | Wld(df = 17) = 16.145, p-val = 0.514 | ||
LRT(df = 17) = 37.990, p-val = 0.002 | LRT(df = 17) = 37.990, p-val = 0.002 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -4.812 | + | -4.812 |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 16) = 15.812, p-val = 0.466 | Q(df = 16) = 15.812, p-val = 0.466 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -0.980 | + | -0.980 |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 16) = 11.866, p-val = 0.753 | Wld(df = 16) = 11.866, p-val = 0.753 | ||
LRT(df = 16) = 28.609, p-val = 0.027 | LRT(df = 16) = 28.609, p-val = 0.027 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -1.353 | + | -1.353 |
--- | --- | ||
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Since the likelihood for studies with zero events is flat, such studies are automatically dropped by the '' | Since the likelihood for studies with zero events is flat, such studies are automatically dropped by the '' | ||
- | Finally, using the approximation to the exact likelihood, we can fit the same model with: | + | Finally, using the approximation to the exact likelihood, we can fit the same model with: |
<code rsplus> | <code rsplus> | ||
res <- rma.glmm(measure=" | res <- rma.glmm(measure=" | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 16) = 11.115, p-val = 0.802 | Wld(df = 16) = 11.115, p-val = 0.802 | ||
LRT(df = 16) = 27.392, p-val = 0.037 | LRT(df = 16) = 27.392, p-val = 0.037 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -1.303 | + | -1.303 |
--- | --- | ||
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dat | dat | ||
</ | </ | ||
- | (I copy the dataset into ' | + | (I copy the dataset into ' |
<code output> | <code output> | ||
study authors year x1i t1i x2i t2i | study authors year x1i t1i x2i t2i | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 8) = 36.384, p-val < .001 | Q(df = 8) = 36.384, p-val < .001 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 8) = 25.427, p-val = 0.001 | Q(df = 8) = 25.427, p-val = 0.001 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 8) = 36.384, p-val < .001 | Wld(df = 8) = 36.384, p-val < .001 | ||
LRT(df = 8) = 38.330, p-val < .001 | LRT(df = 8) = 38.330, p-val < .001 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 8) = 25.427, p-val = 0.001 | Wld(df = 8) = 25.427, p-val = 0.001 | ||
LRT(df = 8) = 44.488, p-val < .001 | LRT(df = 8) = 44.488, p-val < .001 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | | + | |
--- | --- | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Test for Heterogeneity: | + | Test for Heterogeneity: |
Q(df = 8) = 9.698, p-val = 0.287 | Q(df = 8) = 9.698, p-val = 0.287 | ||
Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -0.396 | + | -0.396 |
--- | --- | ||
- | Signif. codes: | + | Signif. codes: |
</ | </ | ||
And the estimated average log incidence rate ratio (i.e., $\hat{\mu} = -0.396$) can again be back-transformed through exponentiation: | And the estimated average log incidence rate ratio (i.e., $\hat{\mu} = -0.396$) can again be back-transformed through exponentiation: | ||
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H^2 (total variability / sampling variability): | H^2 (total variability / sampling variability): | ||
- | Tests for Heterogeneity: | + | Tests for Heterogeneity: |
Wld(df = 8) = 9.698, p-val = 0.287 | Wld(df = 8) = 9.698, p-val = 0.287 | ||
LRT(df = 8) = 11.602, p-val = 0.170 | LRT(df = 8) = 11.602, p-val = 0.170 | ||
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Model Results: | Model Results: | ||
- | estimate | + | estimate |
- | -0.476 | + | -0.476 |
--- | --- |
analyses/stijnen2010.txt · Last modified: 2022/08/03 11:22 by Wolfgang Viechtbauer